The Scientific Study of Religion: Its Contribution to the Study of the <i>Bhagavadg?tā</i>
Bibliographic record
Abstract
Abstract. The Bhagavadg?tā is a popular Hindu text containing eighteen chapters. It begins with the hero, Arjuna, showing a marked unwillingness to engage in combat on the eve of battle. He is finally persuaded to do so by Krishna, who is an incarnation of God. Krishna actually reveals himself as such to an amazed Arjuna in the eleventh chapter. The fact that Arjuna does not immediately heed Krishna's advice to engage in battle after Krishna's sensational self‐disclosure has long puzzled students of the text. It is only at the end of the eighteenth chapter that Arjuna finally shows his readiness to fight. In this essay I argue that the discussion of the nine primary sensory states by Eugene d'Aquili may help resolve this issue and thus provide an instance of a case in which modern scientific study of religion enhances our understanding of a religious phenomenon, as a corrective to the usual charge that it must invariably diminish it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".